• International Journal of Knowledge Content Development & Technology
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• v.7 no.3
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• pp.5-27
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• 2017

Retrieval of scholarly articles about a specific research issue is a routine job of researchers to cross-validate the evidence about the issue. Two articles that focus on a research issue should share similar terms in their core contents, including their goals, backgrounds, and conclusions. In this paper, we present a technique CCSE ($\underline{C}ore$ $\underline{C}ontent$ $\underline{S}imilarity$ $\underline{E}stimation$) that, given an article a, recommends those articles that share similar core content terms with a. CCSE works on titles and abstracts of articles, which are publicly available. It estimates and integrates three kinds of similarity: goal similarity, background similarity, and conclusion similarity. Empirical evaluation shows that CCSE performs significantly better than several state-of-the-art techniques in recommending those biomedical articles that are judged (by domain experts) to be the ones whose core contents focus on the same research issues. CCSE works for those articles that present research background followed by main results and discussion, and hence it may be used to support the identification of the closely related evidence already published in these articles, even when only titles and abstracts of the articles are available.

• Journal of Korea Multimedia Society
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• v.22 no.11
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• pp.1313-1323
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• 2019

With the development of the Internet and the increase of smart phones, various services considering user convenience are increasing, so that users can check news in real time anytime and anywhere. However, online news is categorized by media and category, and it provides only a few related search terms, making it difficult to find related news related to keywords. In order to solve this problem, we propose a method to recommend related documents more accurately by applying Doc2Vec similarity to the specific keywords of news articles and weighting the title and contents of news articles. We collect news articles from Naver politics category by web crawling in Java environment, preprocess them, extract topics using LDA modeling, and find similarities using Doc2Vec. To supplement Doc2Vec, we apply TF-IDF to obtain TC(Title Contents) weights for the title and contents of news articles. Then we combine Doc2Vec similarity and TC weight to generate TC weight-similarity and evaluate the similarity between words using PMI technique to confirm the keyword association.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.1
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• pp.82-88
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• 2017

Recently recommendation methods need personalization and diversity as well as accuracy whereas the traditional researches have been mainly focused on the accuracy of recommendation in terms of quality. The diversity of recommendation is also important to people in terms of quantity in addition to quality since people's desire for content consumption have been stronger rapidly than past. In this paper, we pay attention to similarity of data gathered simultaneously among different types of contents. With this motivation, we propose an enhanced recommendation method using correlation analysis with considering data similarity between two types of contents which are movie and music. Specifically, we regard folksonomy tags for music as correlated data of genres for movie even though they are different attributes depend on their contents. That is, we make result of new recommendation movie items through mapping music folksonomy tags to movie genres in addition to the recommendation items from the typical collaborative filtering. We evaluate effectiveness of our method by experiments with real data set. As the result of experimentation, we found that the diversity of recommendation could be extended by considering data similarity between music contents and movie contents.

• The Journal of the Korea Contents Association
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• v.9 no.2
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• pp.43-50
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• 2009

We proposed similarity detection method of the video frame data that extracts the feature data of own video frame and creates the 1-D signal in this paper. We get the similar frame boundary and make the representative frames within the frame boundary to extract the similarity extraction between video. Representative frames make blurring frames and extract the feature data using DOG values. Finally, we convert the feature data into the 1-D signal and compare the contents similarity. The experimental results show that the proposed algorithm get over 0.9 similarity value against noise addition, rotation change, size change, frame delete, frame cutting.

• The Journal of the Korea Contents Association
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• v.11 no.11
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• pp.378-389
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• 2011

This study scrutinizes the similarity difference between parent brand product and extended brand product of franchise business and its effect on the attitude toward extended brand product. Results showed that the similarity difference is appeared according to product extended. The cognitive attitude and the behavioral attitude toward similarity difference are also appeared to be different as high in product similarity leads to high in both cognitive and behavioral attitude. The result also showed that the food similarity compare to the technological similarity has higher impact on attitude. These study results provided a significant insights in brand extension strategy of franchise business.

• The Journal of the Korea Contents Association
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• v.22 no.10
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• pp.563-574
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• 2022

The purpose of this study is to investigate effects of source credibility of political youtubers on attitude toward contents and politicians/political party and political decision making. The total number of 326 responses from online survey were analyzed. Results indicate that three factors of source credibility, similarity, charisma, and expertise positively affected attitude toward political contents on youtube in statistical significance. Five attributes of source credibility, familiarity, charisma, similarity, attractiveness, and trustworthiness positively affected attitude toward political youtube contents and politicians/political parties. Furthermore, attitude toward contents and politicians/political parties significantly increased voting intention to politicians/political parties.

• Journal of Information Technology Services
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• v.10 no.2
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• pp.281-292
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• 2011

Many online stores provide relevant products in product pages or other pages to attract customer interests. Association rules based on customer purchases and personalized recommendations are most prominently used ways of providing relevant products. Though there have been many studies to apply tags of products as metadata of the products, there are few studies to investigate contents similarities between the products and the suggested products. Thus, this study collects books in purchase associations and their tags in Amazon.com and assesses the similarities between the books. We found out that the contents similarities based on tags are similar among business, literature, and computer networks. And the similarity is also similar among the relevant books that have different ranks.

• Journal of Educational Research in Mathematics
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• v.19 no.1
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• pp.1-24
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• 2009

The applications of ratio and similarity have been in need of everyday life from ancient times. Euclid's elements Ⅴand Ⅵ cover ratio and similarity respectively. In this note, we have done a comparative analysis to button down the contents of ratio and similarity covered by the math text books used in Korea, Euclid's elements and the math text books used in Japan and America. As results, we can observe some differences between them. When math text books used in Korea introduce ratio, they presented it by showing examples unlike math text books used in America and Japan which present ratio by explaining the definition of it. In addition, in the text books used in Korea and Japan, the order of dealing with condition of similarity of triangles and the triangle proportionality is different from that of the text books used in America. Also, condition of similarity of triangles is used intuitively as postulate without any definition in text books used in Korea and Japan which is different from America's. The manner of teaching depending on the way of introducing learning contents and the order of presenting them can have great influence on student's understanding and application of the learning contents. For more desirable teaching in math it is better to provide text books dealing with various learning contents which consider student's diverse abilities rather than using current text books offering learning contents which are applied uniformly.

• Proceedings of the Korean Society of Computer Information Conference
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• 2016.07a
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• pp.219-220
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• 2016

본 논문에서는 컴퓨터비전 기술 기반의 라이브러리를 이용해 미아 얼굴 정보를 중심으로 매칭을 하는 시스템으로서, 미아 데이터베이스에 등록된 얼굴과 유사한 미아를 정확도 순으로 배열해 주는 시스템을 개발한다. 이는 기존의 텍스트 정보 중심의 미아에 대한 정보 등록 및 조회를 하게 되었을 때 발생하는 정보의 부정확성 등의 문제점을 해결하고 편하고 빠르고 정확하게 정보 입력과 매칭을 함으로써 골든 타임 안에 미아를 찾을 수 있는 장점이 있다.

• International Journal of Contents
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• v.13 no.4
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• pp.70-79
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• 2017

Images are an important element in patents and many experts use images to analyze a patent or to check differences between patents. However, there is little research on image analysis for patents partly because image processing is an advanced technology and typically patent images consist of visual parts as well as of text and numbers. This study suggests two methods for using image processing; the Scale Invariant Feature Transform(SIFT) algorithm and Optical Character Recognition(OCR). The first method which works with SIFT uses image feature points. Through feature matching, it can be applied to calculate the similarity between documents containing these images. And in the second method, OCR is used to extract text from the images. By using numbers which are extracted from an image, it is possible to extract the corresponding related text within the text passages. Subsequently, document similarity can be calculated based on the extracted text. Through comparing the suggested methods and an existing method based only on text for calculating the similarity, the feasibility is achieved. Additionally, the correlation between both the similarity measures is low which shows that they capture different aspects of the patent content.